Search | TVST | ARVO Journals

Showing 1 – 20 of 50

SORT: Best Match Most Recent Oldest

VIEW: Basic | Expanded

ARVO Annual Meeting Abstract June 2020

Glance: A Visual Analytics Approach for Opening the Black Box to Explain Deep Learning Predictions of Glaucomatous Visual Field Damage from Optical Coherence Tomography Scans

Astrid van den Brandt; Mark Christopher; Jasmin Rezapour; Derek S. Welsbie; Andrew S. Camp; Sally L. Baxter; Jiun Do; Sasan Moghimi; Akram Belghith; Christopher Bowd; Michael Henry Goldbaum; Robert N Weinreb; Michel A. Westenberg; Chris CP Snijders; Linda M Zangwill

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):4527. doi:

ARVO Annual Meeting Abstract June 2020

Individualized deep learning auto-encoder (DL-AE)-based OCT deviation maps for improved glaucoma progression detection

Christopher Bowd; Akram Belghith; Mark Christopher; Michael Henry Goldbaum; Massimo Antonio Fazio; Christopher A Girkin; Jeffrey M Liebmann; C Gustavo De Moraes; Robert N Weinreb; Linda M Zangwill

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):4536. doi:

ARVO Annual Meeting Abstract June 2020

Predicting glaucoma prior to its onset using deep learning

Anshul Thakur; Michael Henry Goldbaum; Siamak Yousefi

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):876. doi:

ARVO Annual Meeting Abstract June 2020

Deep Learning Models Based on Unsegmented OCT RNFL Circle Scans Provide Accurate Detection of Glaucoma and High Resolution Prediction of Visual Field Damage

Mark Christopher; James Alexander Proudfoot; Christopher Bowd; Akram Belghith; Michael Henry Goldbaum; Jasmin Rezapour; Sasan Moghimi; Robert N Weinreb; Massimo Antonio Fazio; Christopher A Girkin; Carlos Gustavo De Moraes; Jeffrey M Liebmann; Linda M Zangwill

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):1439. doi:

ARVO Annual Meeting Abstract June 2020

Deep Learning Models Predict Age, Sex and Race from OCT Optic Nerve Head Circle Scans

LeAnn Mendoza; Mark Christopher; Akram Belghith; Christopher Bowd; Jasmin Rezapour; Massimo A Fazio; Michael Henry Goldbaum; Robert Weinreb; Christopher A Girkin; Jeffrey M Liebmann; C Gustavo De Moraes; Linda M Zangwill

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):2012. doi:

Special Issue April 2020

Effects of Study Population, Labeling and Training on Glaucoma Detection Using Deep Learning Algorithms

PDF

Mark Christopher; Kenichi Nakahara; Christopher Bowd; James A. Proudfoot; Akram Belghith; Michael H. Goldbaum; Jasmin Rezapour; Robert N. Weinreb; Massimo A. Fazio; Christopher A. Girkin; Jeffrey M. Liebmann; Gustavo De Moraes; Hiroshi Murata; Kana Tokumo; Naoto Shibata; Yuri Fujino; Masato Matsuura; Yoshiaki Kiuchi; Masaki Tanito; Ryo Asaoka; Linda M. Zangwill
TAGS: datasets, deep learning, glaucoma, training, study population
Trans. Vis. Sci. Tech.. 2020; 9(2):27. doi: https://doi.org/10.1167/tvst.9.2.27

Includes: Supplemental Content

ARVO Annual Meeting Abstract July 2019

Frequency of Mismatch Repair Gene Mutations in Uveal Melanoma

Christopher Brian Toomey; Samantha Phou; Kyle Fraser; Mathieu Bakhoum; John A Thorson; Bobby S Korn; Don Osami Kikkawa; Michael Henry Goldbaum; Jonathan H Lin

Invest. Ophthalmol. Vis. Sci.. 2019; 60(9):761. doi:

ARVO Annual Meeting Abstract July 2019

Morphology of Retinal Pathologic Prion Protein (PrP) Deposits in Sporadic Creutzfeldt-Jakob Disease (sCJD) Patients

Adeleh Yarmohammadi; Vanessa Goodwill; Christina sigurdson; Michael Henry Goldbaum; Peter Savino; Jonathan H Lin

Invest. Ophthalmol. Vis. Sci.. 2019; 60(9):3542. doi:

ARVO Annual Meeting Abstract July 2019

Dilatation of the retinal capillary plexuses in branch retinal vein occlusion

Christopher Patrick Long; Mathieu Bakhoum; Christopher Brian Toomey; Dirk-Uwe G Bartsch; Eric Nudleman; Michael Henry Goldbaum; K Bailey Freund; David Sarraf; William R Freeman

Invest. Ophthalmol. Vis. Sci.. 2019; 60(9):5736. doi:

ARVO Annual Meeting Abstract July 2019

Deep Learning Models Predict Visual Function from Macula Thickness Map

Mark Christopher; Akram Belghith; Christopher Bowd; Massimo Antonio Fazio; Michael Henry Goldbaum; Robert N Weinreb; Christopher A Girkin; Jeffrey M Liebmann; Linda M Zangwill

Invest. Ophthalmol. Vis. Sci.. 2019; 60(9):5600. doi:

ARVO Annual Meeting Abstract July 2019

Diagnostic accuracy of OCTA vessel density and OCT tissue thickness measurements using machine learning

Christopher Bowd; Akram Belghith; Linda M Zangwill; Michael Henry Goldbaum; Mark Christopher; Elham Ghahari; Huiyuan Hou; Sasan Moghimi; Rafaella Penteado; Robert N Weinreb

Invest. Ophthalmol. Vis. Sci.. 2019; 60(9):3044. doi:

ARVO Annual Meeting Abstract July 2018

Deep Learning Approaches Can Detect Glaucomatous Functional Loss better than standard SD-OCT Retinal Nerve Fiber Layer Thickness

Mark Christopher; Akram Belghith; Christopher Bowd; Michael Henry Goldbaum; Robert N Weinreb; Linda M Zangwill

Invest. Ophthalmol. Vis. Sci.. 2018; 59(9):2090. doi:

ARVO Annual Meeting Abstract July 2018

GNAQ R183Q Mutation Identified in a Young Patient with Uveal Melanoma, Ocular Surface Melanosis, and Nevus of Ota

Christopher Brian Toomey; Kyle Fraser; Christina DiLoreto; Wesleigh Edwards; John A Thorson; Don Kikkawa; Michael Henry Goldbaum; Jonathan H Lin

Invest. Ophthalmol. Vis. Sci.. 2018; 59(9):3187. doi:

ARVO Annual Meeting Abstract July 2018

Reproducibility of AngioAnalytics Measurements of OCTA Retina Scans in Normal, Glaucoma and Diabetic Retinopathy Eyes

Yulia Wolfson; Eric Nudleman; Michael Henry Goldbaum; Linda M Zangwill; Jing Tian; Kelly A Soules; Ben K Jang; Robert N Weinreb; Qienyuan Zhou

Invest. Ophthalmol. Vis. Sci.. 2018; 59(9):2875. doi:

ARVO Annual Meeting Abstract July 2018

Gaussian Mixture Model Expectation Maximization for Glaucoma Progression Detection: An open-source R Package

Edward De Guzman; Christopher Bowd; Michael Henry Goldbaum; Golnoush Sadat Mahmoudi Nezhad; Siamak Yousefi

Invest. Ophthalmol. Vis. Sci.. 2018; 59(9):5116. doi:

Glaucoma June 2018

Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression

PDF

Mark Christopher; Akram Belghith; Robert N. Weinreb; Christopher Bowd; Michael H. Goldbaum; Luke J. Saunders; Felipe A. Medeiros; Linda M. Zangwill
TAGS: glaucoma, retinal nerve fiber layer, optical coherence tomography, unsupervised machine learning
Invest. Ophthalmol. Vis. Sci.. 2018; 59(7):2748-2756. doi: https://doi.org/10.1167/iovs.17-23387

ARVO Annual Meeting Abstract June 2017

Digitally Assisted Vitreoretinal Surgery using the NGENUITY 3-D System

William R Freeman; Joseph Ho; Daniel Chao; Michael Henry Goldbaum; Henry Ferreyra; Burton Tripathi; Eric Nudleman

Invest. Ophthalmol. Vis. Sci.. 2017; 58(8):1186. doi:

ARVO Annual Meeting Abstract June 2017

Comparison of FISH and Cytogenomic Microarray Analysis for Detection of Chromosomal Abnormalities in Uveal Melanoma

Faris Hashem; Nosaibah Hariri; James Solomon; John Thorson; Marie Dell'Aquila; Bobby Korn; Don Kikkawa; Michael Henry Goldbaum; Jonathan Lin

Invest. Ophthalmol. Vis. Sci.. 2017; 58(8):3962. doi:

ARVO Annual Meeting Abstract June 2017

Computational Features Derived from Retinal Nerve Fiber Layer (RNFL) Thickness Maps in Detecting and Monitoring Glaucoma

Mark Christopher; Akram Belghith; Christopher Bowd; Michael Henry Goldbaum; Luke J Saunders; Felipe Medeiros; Robert N Weinreb; Linda M Zangwill

Invest. Ophthalmol. Vis. Sci.. 2017; 58(8):3999. doi:

ARVO Annual Meeting Abstract September 2016

Early detection of visual field conversion using an unsupervised machine-learning analysis of retinal nerve fiber layer thickness measurements

Siamak Yousefi; Michael Henry Goldbaum; Ehsan Shahrian Varnousfaderani; Linda M Zangwill; Felipe A Medeiros; Robert N Weinreb; Christopher A Girkin; Jeffrey M Liebmann; Christopher Bowd

Invest. Ophthalmol. Vis. Sci.. 2016; 57(12) doi:

1 2 3

Next 20 Results »

NARROW

Content Type

Journal

Article Type

Topics

Tags

Specify Date Range

Glance: A Visual Analytics Approach for Opening the Black Box to Explain Deep Learning Predictions of Glaucomatous Visual Field Damage from Optical Coherence Tomography Scans

Individualized deep learning auto-encoder (DL-AE)-based OCT deviation maps for improved glaucoma progression detection

Predicting glaucoma prior to its onset using deep learning

Deep Learning Models Based on Unsegmented OCT RNFL Circle Scans Provide Accurate Detection of Glaucoma and High Resolution Prediction of Visual Field Damage

Deep Learning Models Predict Age, Sex and Race from OCT Optic Nerve Head Circle Scans

Effects of Study Population, Labeling and Training on Glaucoma Detection Using Deep Learning Algorithms

Frequency of Mismatch Repair Gene Mutations in Uveal Melanoma

Morphology of Retinal Pathologic Prion Protein (PrP) Deposits in Sporadic Creutzfeldt-Jakob Disease (sCJD) Patients

Dilatation of the retinal capillary plexuses in branch retinal vein occlusion

Deep Learning Models Predict Visual Function from Macula Thickness Map

Diagnostic accuracy of OCTA vessel density and OCT tissue thickness measurements using machine learning

Deep Learning Approaches Can Detect Glaucomatous Functional Loss better than standard SD-OCT Retinal Nerve Fiber Layer Thickness

GNAQ R183Q Mutation Identified in a Young Patient with Uveal Melanoma, Ocular Surface Melanosis, and Nevus of Ota

Reproducibility of AngioAnalytics Measurements of OCTA Retina Scans in Normal, Glaucoma and Diabetic Retinopathy Eyes

Gaussian Mixture Model Expectation Maximization for Glaucoma Progression Detection: An open-source R Package

Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression

Digitally Assisted Vitreoretinal Surgery using the NGENUITY 3-D System

Comparison of FISH and Cytogenomic Microarray Analysis for Detection of Chromosomal Abnormalities in Uveal Melanoma

Computational Features Derived from Retinal Nerve Fiber Layer (RNFL) Thickness Maps in Detecting and Monitoring Glaucoma

Early detection of visual field conversion using an unsupervised machine-learning analysis of retinal nerve fiber layer thickness measurements

To View More...

You must be signed into an individual account to use this feature.